Heating Operation Scheduling Robust Optimization Model for Heat Storage Electric Boiler Combined with Wind Power

doi:10.3969/j.issn.1000-7229.2016.01.016

Abstract

Abstract:

To alleviate the influence of wind power uncertainty on the wind power accommodation of systemand improve the utilization efficiency of wind power, we introducethe robust stochastic optimization theory, employ wind power and heat storage electric boilers to set up heating supply system, and construct the heating scheduling optimization model of wind power with taking the uncertainty of wind power into consideration. First of all, we build the model of wind power output and the load demand model of heat storage electric boilers；then, we use the theory of robust stochastic optimization to describe the uncertainty of wind power output, and construct the heating scheduling optimization models of wind power and heat storage electric boilers respectively under the uncertainty and randomness conditions of wind power output. Finally, we choose a wind power heating project in a certain city in the north of China for example analysis. The results show that the robust stochastic optimization theory can effectively describe the uncertainty output of wind power and provide the decision-making tool for different risk attitude decision-makers. The heating system composed of wind power and heat storage electric boiler can realize the heating load flexibly in power system dispatching, increase the accommodation capacity of wind power, and reduce abandoned wind power, which has remarkable economic and environmental benefits.

Key words: wind power, heat storage electric boiler, robust, model

CLC Number:

TM 73

CHEN Shoujun,XIN He,WANG Tao,YANG Jun, PENG Daoxin,TAN Zhongfu. Heating Operation Scheduling Robust Optimization Model for Heat Storage Electric Boiler Combined with Wind Power[J]. Electric Power Construction, 2016, 37(1): 103-109.

References

［1］金灿宝.能源局力挺风电供暖［J］.广西电业,2013（4）:15.
［2］魏晓霞.中国大规模风电接入电网而临的挑战［J］.中国能源，2010(2):19-21.
WEI Xiaoxia. Facing large scale of wind power in our country integrated, our country has great potential for exploitation［J］.China Energy Group, 2010(2):19-21.
［3］王彩霞,李琼慧,谢国辉.风电供热提高低谷风电消纳能力评估［J］.中国电力,2013,46(12):100-106.
WANG Caixia, LI Qionghui, XIE Guohui. Evaluation of windpower heating in facilitating wind power integration capabilityduring valley load period［J］. Electric Power, 2013, 46(12): 100-106.
［4］黄怡，张义斌，孙强，等.适应中国风电高速发展的举措建议［J］.能源技术经济，2010,22(3):18-21.
HUANG Yi, ZHANG Yibin, SUN Qiang, et al. Some suggestions on the measures for high-speed wind power development in China ［J］. Energy Technology and Economics, 2010,22(3):18-21.
［5］尹明，王成山，葛旭波.风电并网经济技术评价研究综述［J］.电力系统及其自动化学报，2010,22(5):103-108.
YIN Ming，WANG Chengshan，GE Xubo. Review of economic-technical assessment of wind power intergration［J］.Proceedings of the CSU-EPSA，2010，22(5) : 102-108.
［6］侯德席,张健,王曼莉.蓄热式电供暖技术经济性分析［J］. 煤气与热力,2010,30(10):21-23.
HOU Dexi, ZHANG Jian, WANG Manli. Technical and economic analysis on regenerative electricheating technology［J］. Gas ＆ Heat, 2010,30(10):21-23.
［7］高晓林,翁文兵,郏京武,等.地源热泵与蓄热式电锅炉冬季制热的节能性实测与分析［J］.建筑节能, 2012, 40(2):9-12.
GAO Xiaolin, WENG Wenbing, JIA Jingwu, et al. Energy-saving measuring and analysis with the GSHP and the electric boiler for a heating system in a certain office building of Shanghai in winter ［J］. Building Energy Efficiency, 2012,40(2):9-12.
［8］谈小灵.浅谈电采暖技术的优越性［J］.煤炭工程，2006(8):64-65.
TAN Xiaoling. Advantages of electric heating technology ［J］. Coal Engineering, 2006(8):64-65.
［9］肖明东，余莉，滕力.电锅炉蓄热技术在某供暖工程中的应用［J］.暖通空调，2004, 34 (1): 65- 66.
XIAO Mingdong, YU Li, TENG Li. Application of electric heat storage boiler in a project ［J］. Heating Ventilating & Air Condictioning, 2004, 34 (1): 65- 66.
［10］艾欣,刘晓. 基于需求响应的风电消纳机会约束模型研究［J］. 华北电力大学学报：自然科学版, 2011,38(3):17-22.
AI Xin, LIU Xiao. Chance constrained model for wind power usage based on demand response ［J］. Journal of North China Electric Power University: Natural Science Edition, 2011,38(3):17-22.
［11］白牧可,唐巍,张璐,等. 基于机会约束规划的DG与配电网架多目标协调规划［J］. 电工技术学报,2013,28(10):346-354.
BAI Muke, TANG Wei, ZHANG Lu, et al. Multi-objective coordinated planning of distribution network incorporating distributed generation based on chance constrained programming ［J］. Transactions of China Electrotechnical Society, 2013,28(10):346-354.
［12］张海峰,高峰,吴江,等.含风电的电力系统动态经济调度模型［J］.电网技术,2013,37(5):1298-1303.
ZHANG Haifeng, GAO Feng, WU Jiang, et al. A dynamic economic dispatching model for power grid containing wind power generation system ［J］. Power System Technology, 2013,37(5):1298-1303.
［13］杨楠,王波,刘涤尘, 等.考虑柔性负荷调峰的大规模风电随机优化调度方法［J］.电工技术学报,2013,28(11):231-238.
YANG Nan, WANG Bo, LIU Dichen, et al. Large-scale wind power stochastic optimization scheduling methodconsidering flexible load peaking ［J］. Transactions of China Electrotechnical Society, 2013,28(11):231-238.

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